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Design of computer tomograph
Bojková, Eva ; Lehocký, Peter (referee) ; Zvonek, Miroslav (advisor)
The graduation thesis is engaged in the design of computed tomography (CT). It is a piece of medical equipment which helps to define the diagnosis of a patient. The first part of the project is a research into contemporary stage and production of CT systems. Consequently the new design of computed tomography is designed in a way to maximise ergonomical, technical and aesthetic quality.
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Identification of vertebrae type in CT data by machine learning methods
Matoušková, Barbora ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
Identification of vertebrae type by machine learning is an important task to facilitate the work of medical doctors. This task is embarrassed by many factors. First, a spinal CT imagining is usually performed on patiens with pathologies such as lesions, tumors, kyphosis, lordosis, scoliosis or patients with various implants that cause artifacts in the images. Furthermore, the neighboring vertebraes are very similar which also complicates this task. This paper deals with already segmented vertebrae classification into cervical, thoracic and lumbar groups. Support vector machines (SVM) and convolutional neural networks (CNN) AlexNet and VGG16 are used for classification. The results are compared in the conclusion.
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Segmentation of ribs in thoracic CT scans
Kašík, Ondřej ; Kolář, Radim (referee) ; Jakubíček, Roman (advisor)
This thesis deals with design and implementation of an algorithm for segmentation of ribs from thoracic CT data. For the segmentation method of rib centerlines detection is chosen. The first step of this approach is to extract the centerlines of all the bones located in the scan. These centerlines are divided into short primitives, which are subsequently classified into couple of categories, depending on whether they represent the centerline of the rib. Subsequently, the centrelines of ribs are used as the seed points of the region growing algorithm in three-dimensional space, which realizes the final segmentation of the ribs. Within the work, a database of 10 CT scans was manually annotated, which was subsequently used to validate a performance of the proposed segmentation approach. The achieved success rate of primitive classification is 96,7 %, the success rate of rib segmentation (Dice coefficient) is 86,8 %.
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Contour Shape Classification for Detection of Mis-Segmented bones in CT Data
Janovič, Tomáš ; Jan, Jiří (referee) ; Walek, Petr (advisor)
The thesis discusses the possibilities of using contour shape classification for detection of mis-segmented bones in computed tomography (CT) data. In the first part there are presented published methods and algorithms which deal with the segmentation of bone structures in CT data. Then segmentation of cortical bones is implemented by a simple thresholding with global threshold. The threshold is determined by the optimized fitting of a selected type probability distribution to the histogram. Subsequently, the thesis describes some important shape descriptors that can quantitatively describe the shapes of objects in the image. Further, the contour extraction is implemented and a suitable shape descriptor, cumulative angular function, is applied. Finally, the points which can potentially indicate mis-segmented bones are detected by using continuous wavelet transform. The proposed technique is tested on the real CT data.
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Stress strain analysis of the femur based on the CT data collection
Nečas, David ; Marcián, Petr (referee) ; Vosynek, Petr (advisor)
The area of clinical biomechanics is a rapidly growing engineering discipline in the world of today. This master's thesis is concerned with the stress-strain analysis of human femoral neck. In the first place it emphasizes the creation of computational model, especially the model of bone material, because of its high level of inhomogeneity. The creation of the computational model has been tested using several software packages, which are often mentioned in connection with the biomechanical tasks. The latter part of the thesis contains finite element method analysis for several material models, which are based on extensive analysis of relations used to transfer the information from computed tomography data to material model properties. Subsequently, the realization of experimental measurement is described. The final part of the thesis contains evaluated results obtained from the FEM analysis, which are also compared with the experiment.
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Segmentation of cerebral vessels in volumetric data
Sucháček, Jan ; Harabiš, Vratislav (referee) ; Jakubíček, Roman (advisor)
This thesis deals with the design, implementation and testing of an algorithm for segmentation of cerebral vessels in 3D CT image data with a focus on stroke. First, a 3D binary mask of the brain was created and then used to extract brain tissue from the original volumetric CT images. In the extracted brain tissue, cerebral vessels were enhanced using three advanced filters based on Hessian matrix calculation and eigenvalue analysis of the Hessian matrix. The resulting parametric images of the enhanced cerebral vessels were input to six segmentation methods that were implemented and compared in this work. The program solution of this work was implemented in Matlab R2021b. The proposed algorithm was tested on real patient data. In one of the patient CT scans, cerebral vessels were labeled as part of this thesis and this resulting volume of manually segmented cerebral vessels was used to objectively evaluate the segmentation results obtained. In the theoretical part, the anatomy, physiology and pathology of the cerebral vascular supply were studied and described. Furthermore, the imaging methods used for imaging the cerebral vascular supply were described. A review of available segmentation techniques and specific approaches already published for segmentation of the cerebral vascular supply was performed. The methods used in this thesis were also theoretically described.
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Utilisation of shape analysis methods for object classification in medical images
Karela, Jiří ; Odstrčilík, Jan (referee) ; Chmelík, Jiří (advisor)
Bachelor thesis deals with problems of shape analysis. It describes some procedures and methods related to this kind of analysis. The thesis is divided into theoretical part, practical part and conclusion. In the theoretical part we describe in greater detail some methods, with the help of which the practical part was solved. But other theories related to the topic are also described. The practical part then follows the given theory and solves the problem of shape analysis due to the knowledge gained in the theory. The algorithm is tested on medical data from CT of vertebrae. The conclusion serves as a summary and evaluation of the shape analysis solution. It also serves as a reflection on the realization of our method, ie how our solution and result could be improved.
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Emerging Trends in Dendrochronology
Horáček, Tomáš ; Neuwirthová, Ludmila (referee) ; Mikulka, Jan (advisor)
Tato práce se zabývá popisem současných a experimentálních metod odběru vzorků pomocí presslerova nebozezu, výřezů z kmene, fotografie, rentgenu, počítačové tomografie a magnetické rezonance na poli dendrochronologického výzkumu. V práci jsou rozebírány destruktivní a nedesktruktivní metody odběru vzorků. Je také kladen důraz na původ vzorků: zdali je možno využít destruktivní metody nebo zdali je to nemožné jako v případě vzácných archeologických objektů. Dále popisuje standardní optometrickou metody a další experimentální metody fungujicí na principu kontranstního zpracování obrazu za účelem rozeznání letokruhů. V práci jsou také popsány různé druhy metod softwarového zpracovnání kde jako vstup slouží buď série dat nebo obraz letokruhů. Další rozdíly tvoří vymezené spektrum uvedených prací, některé práce se zaměřují na zpracování obrazu od píky tedy od pořízené fotografie až po hotové datovaní, některé však zajímá pouze úzký sektor dendrochronologie jako jsou například vady či špatně rozeznatelné letokruhy.
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Utilisation of phase contrast in X-ray computed tomography
Kalasová, Dominika ; Švéda,, Libor (referee) ; Zikmund, Tomáš (advisor)
X-ray computed tomography is a nondestructive method for 3D imaging of inner structure of objects; it is, however, restricted by absorption properties of materials. With phase contrast imaging, observation of samples with low absorption or with parts with similar absorption becomes possible. For a long time, phase contrast imaging has been restricted to synchrotron radiation sources or special techniques due to requirement of spatial coherence of radiation. Along with recent development of X-ray micro and nanofocus tubes and X-ray detectors a phase contrast imaging becomes available also with laboratory sources. In this work an overview of phase contrast imaging methods is given, with an emphassis on propagation based method. Examples of this method and application of phase retrieval algorithm on samples from RIGAKU Nano3DX and GE phoenix v|tome|x L240 stations within Laboratory of X-ray micro and nanotomography CEITEC BUT are shown.
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